Enhancing Business Decision-Making through AI Augmented Analytics Using Power BI Copilot

International Journal of Computer Science and Engineering

© 2025 by SSRG - IJCSE Journal

Volume 12 Issue 8

Year of Publication : 2025

Authors : Harsh Bhagwandas Patel

10.14445/23488387/IJCSE-V12I8P102

How to Cite?

Harsh Bhagwandas Patel, "Enhancing Business Decision-Making through AI Augmented Analytics Using Power BI Copilot," SSRG International Journal of Computer Science and Engineering , vol. 12,  no. 8, pp. 13-20, 2025. Crossref, https://doi.org/10.14445/23488387/IJCSE-V12I8P102

Abstract:

The integration of large language models with business intelligence platforms represents an important shift toward AI-augmented analytics, making faster and more accessible decision-making. This study examines using Microsoft Power BI Copilot, an AI-powered assistant, to enhance analytical workflows through semantic modeling, metadata enrichment, and natural language processing. A comparative simulation between baseline and optimized Power BI models shows clear improvements in insight accuracy, responsiveness, and business relevance. The paper further compares Copilot's performance against models such as CoddLLM and GPT-4 for SQL generation and narrative outputs. The findings suggest that AI can strengthen business intelligence by increasing return on investment, reducing time-to-insight, and expanding analytics adoption across user roles. This work contributes to the field of decision intelligence by providing practical observations and considerations of deploying AI-augmented analytics in enterprise environments.

Keywords:

AI-Augmented analytics, Business intelligence, Copilot, Decision intelligence, Generative AI, Large language models, Semantic modeling.

References:

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